Pub Date : 2010-05-03DOI: 10.1109/MSST.2010.5496985
A. Jagmohan, M. Franceschini, L. Lastras
The block erase requirement in NAND Flash devices leads to the need for garbage collection. Garbage collection results in write amplification, that is, to an increase in the number of physical page programming operations. Write amplification adversely impacts the limited lifetime of a NAND Flash device, and can add significant system overhead unless a large spare factor is maintained. This paper proposes a NAND Flash system which uses multi-write coding to reduce write amplification. Multi-write coding allows a NAND Flash page to be written more than once without requiring an intervening block erase. We present a novel two-write coding technique based on enumerative coding, which achieves linear coding rates with low computational complexity. The proposed technique also seeks to minimize memory wear by reducing the number of programmed cells per page write. We describe a system which uses lossless data compression in conjunction with multi-write coding, and show through simulations that the proposed system has significantly reduced write amplification and memory wear.
{"title":"Write amplification reduction in NAND Flash through multi-write coding","authors":"A. Jagmohan, M. Franceschini, L. Lastras","doi":"10.1109/MSST.2010.5496985","DOIUrl":"https://doi.org/10.1109/MSST.2010.5496985","url":null,"abstract":"The block erase requirement in NAND Flash devices leads to the need for garbage collection. Garbage collection results in write amplification, that is, to an increase in the number of physical page programming operations. Write amplification adversely impacts the limited lifetime of a NAND Flash device, and can add significant system overhead unless a large spare factor is maintained. This paper proposes a NAND Flash system which uses multi-write coding to reduce write amplification. Multi-write coding allows a NAND Flash page to be written more than once without requiring an intervening block erase. We present a novel two-write coding technique based on enumerative coding, which achieves linear coding rates with low computational complexity. The proposed technique also seeks to minimize memory wear by reducing the number of programmed cells per page write. We describe a system which uses lossless data compression in conjunction with multi-write coding, and show through simulations that the proposed system has significantly reduced write amplification and memory wear.","PeriodicalId":350968,"journal":{"name":"2010 IEEE 26th Symposium on Mass Storage Systems and Technologies (MSST)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114171964","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2010-05-03DOI: 10.1109/MSST.2010.5496996
B. Wongchaowart, M. Iskander, Sangyeun Cho
Phase-change random access memory (PRAM) is a promising storage-class memory technology that has the potential to replace flash memory and DRAM in many applications. Because individual cells in a PRAM can be written independently, only data cells whose current values differ from the corresponding bits in a write request need to be updated. Furthermore, when a block write request is received, the PRAM may contain many free blocks that are available for overwriting, and these free blocks will generally have different contents. For this reason, the number of bit programming operations required to write new data to the PRAM (and consequently power consumption and write bandwidth) depends on the location that is chosen to be overwritten. This paper describes a block placement algorithm for reducing PRAM bit writes based on the idea of indexing free blocks using a content-based signature; computing the signature value of a new block of data to be written allows a free block with similar contents to be located quickly. While the benefit that can be realized by the use of any block placement algorithm is heavily dependent on the workload, our evaluation results show that block placement using content-based signatures is able to reduce the number of PRAM bit programming operations by as much as an order of magnitude.
{"title":"A content-aware block placement algorithm for reducing PRAM storage bit writes","authors":"B. Wongchaowart, M. Iskander, Sangyeun Cho","doi":"10.1109/MSST.2010.5496996","DOIUrl":"https://doi.org/10.1109/MSST.2010.5496996","url":null,"abstract":"Phase-change random access memory (PRAM) is a promising storage-class memory technology that has the potential to replace flash memory and DRAM in many applications. Because individual cells in a PRAM can be written independently, only data cells whose current values differ from the corresponding bits in a write request need to be updated. Furthermore, when a block write request is received, the PRAM may contain many free blocks that are available for overwriting, and these free blocks will generally have different contents. For this reason, the number of bit programming operations required to write new data to the PRAM (and consequently power consumption and write bandwidth) depends on the location that is chosen to be overwritten. This paper describes a block placement algorithm for reducing PRAM bit writes based on the idea of indexing free blocks using a content-based signature; computing the signature value of a new block of data to be written allows a free block with similar contents to be located quickly. While the benefit that can be realized by the use of any block placement algorithm is heavily dependent on the workload, our evaluation results show that block placement using content-based signatures is able to reduce the number of PRAM bit programming operations by as much as an order of magnitude.","PeriodicalId":350968,"journal":{"name":"2010 IEEE 26th Symposium on Mass Storage Systems and Technologies (MSST)","volume":"78 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124107935","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2010-05-03DOI: 10.1109/MSST.2010.5496979
Kevin R. B. Butler, Stephen E. McLaughlin, P. Mcdaniel
Storage is increasingly becoming a vector for data compromise. Solutions for protecting on-disk data confidentiality and integrity to date have been limited in their effectiveness. Providing authenticated encryption, or simultaneous encryption with integrity information, is important to protect data at rest. In this paper, we propose that disks augmented with non-volatile storage (e.g., hybrid hard disks) and cryptographic processors (e.g., FDE drives) may provide a solution for authenticated encryption, storing security metadata within the drive itself to eliminate dependences on other parts of the system. We augment the DiskSim simulator with a flash simulator to evaluate the costs associated with managing operational overheads. These experiments show that proper tuning of system parameters can eliminate many of the costs associated with managing security metadata, with less than a 2% decrease in IOPS versus regular disks.
{"title":"Disk-enabled authenticated encryption","authors":"Kevin R. B. Butler, Stephen E. McLaughlin, P. Mcdaniel","doi":"10.1109/MSST.2010.5496979","DOIUrl":"https://doi.org/10.1109/MSST.2010.5496979","url":null,"abstract":"Storage is increasingly becoming a vector for data compromise. Solutions for protecting on-disk data confidentiality and integrity to date have been limited in their effectiveness. Providing authenticated encryption, or simultaneous encryption with integrity information, is important to protect data at rest. In this paper, we propose that disks augmented with non-volatile storage (e.g., hybrid hard disks) and cryptographic processors (e.g., FDE drives) may provide a solution for authenticated encryption, storing security metadata within the drive itself to eliminate dependences on other parts of the system. We augment the DiskSim simulator with a flash simulator to evaluate the costs associated with managing operational overheads. These experiments show that proper tuning of system parameters can eliminate many of the costs associated with managing security metadata, with less than a 2% decrease in IOPS versus regular disks.","PeriodicalId":350968,"journal":{"name":"2010 IEEE 26th Symposium on Mass Storage Systems and Technologies (MSST)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130385278","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2010-05-03DOI: 10.1109/MSST.2010.5496975
David O. Bigelow, S. Brandt, John Bent, Hsing-bung Chen
Large radio telescopes, cyber-security systems monitoring real-time network traffic, and others have specialized data storage needs: guaranteed capture of an ultra-high-bandwidth data stream, retention of the data long enough to determine what is “interesting,” retention of interesting data indefinitely, and concurrent read/write access to determine what data is interesting, without interrupting the ongoing capture of incoming data. Mahanaxar addresses this problem. Mahanaxar guarantees streaming real-time data capture at (nearly) the full rate of the raw device, allows concurrent read and write access to the device on a best-effort basis without interrupting the data capture, and retains data as long as possible given the available storage. It has built in mechanisms for reliability and indexing, can scale to meet arbitrary bandwidth requirements, and handles both small and large data elements equally well. Results from our prototype implementation show that Mahanaxar provides both better guarantees and better performance than traditional file systems.
{"title":"Mahanaxar: Quality of service guarantees in high-bandwidth, real-time streaming data storage","authors":"David O. Bigelow, S. Brandt, John Bent, Hsing-bung Chen","doi":"10.1109/MSST.2010.5496975","DOIUrl":"https://doi.org/10.1109/MSST.2010.5496975","url":null,"abstract":"Large radio telescopes, cyber-security systems monitoring real-time network traffic, and others have specialized data storage needs: guaranteed capture of an ultra-high-bandwidth data stream, retention of the data long enough to determine what is “interesting,” retention of interesting data indefinitely, and concurrent read/write access to determine what data is interesting, without interrupting the ongoing capture of incoming data. Mahanaxar addresses this problem. Mahanaxar guarantees streaming real-time data capture at (nearly) the full rate of the raw device, allows concurrent read and write access to the device on a best-effort basis without interrupting the data capture, and retains data as long as possible given the available storage. It has built in mechanisms for reliability and indexing, can scale to meet arbitrary bandwidth requirements, and handles both small and large data elements equally well. Results from our prototype implementation show that Mahanaxar provides both better guarantees and better performance than traditional file systems.","PeriodicalId":350968,"journal":{"name":"2010 IEEE 26th Symposium on Mass Storage Systems and Technologies (MSST)","volume":"358 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116364784","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2010-05-03DOI: 10.1109/MSST.2010.5496993
Doron Chen, George Goldberg, R. Kahn, Ronen I. Kat, K. Meth
Reduction of disk drive power consumption is a challenging task, particularly since the most prevalent way of achieving it, powering down idle disks, has many undesirable side-effects. Some hard disk drives support acoustic modes, meaning they can be configured to reduce the acceleration and velocity of the disk head. This reduces instantaneous power consumption but sacrifices performance. As a result, input/output (I/O) operations run longer at reduced power. This is useful for power capping since it causes significant reduction in peak power consumption of the disks. We conducted experiments on several disk drives that support acoustic management. Most of these disk drives support only two modes — quiet and normal. We ran different I/O workloads, including SPC-1 to simulate a real-world online transaction processing workload. We found that the reduction in peak power can reach up to 23% when using quiet mode. We show that for some workloads this translates into a reduction of 12.5% in overall energy consumption. In other workloads we encountered the opposite phenomenon-an increase of more than 6% in the overall energy consumption.
{"title":"Leveraging disk drive acoustic modes for power management","authors":"Doron Chen, George Goldberg, R. Kahn, Ronen I. Kat, K. Meth","doi":"10.1109/MSST.2010.5496993","DOIUrl":"https://doi.org/10.1109/MSST.2010.5496993","url":null,"abstract":"Reduction of disk drive power consumption is a challenging task, particularly since the most prevalent way of achieving it, powering down idle disks, has many undesirable side-effects. Some hard disk drives support acoustic modes, meaning they can be configured to reduce the acceleration and velocity of the disk head. This reduces instantaneous power consumption but sacrifices performance. As a result, input/output (I/O) operations run longer at reduced power. This is useful for power capping since it causes significant reduction in peak power consumption of the disks. We conducted experiments on several disk drives that support acoustic management. Most of these disk drives support only two modes — quiet and normal. We ran different I/O workloads, including SPC-1 to simulate a real-world online transaction processing workload. We found that the reduction in peak power can reach up to 23% when using quiet mode. We show that for some workloads this translates into a reduction of 12.5% in overall energy consumption. In other workloads we encountered the opposite phenomenon-an increase of more than 6% in the overall energy consumption.","PeriodicalId":350968,"journal":{"name":"2010 IEEE 26th Symposium on Mass Storage Systems and Technologies (MSST)","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114949273","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2010-05-03DOI: 10.1109/MSST.2010.5496981
S. Son, S. Lang, P. Carns, R. Ross, R. Thakur, Berkin Özisikyilmaz, Prabhat Kumar, W. Liao, A. Choudhary
As data sizes continue to increase, the concept of active storage is well fitted for many data analysis kernels. Nevertheless, while this concept has been investigated and deployed in a number of forms, enabling it from the parallel I/O software stack has been largely unexplored. In this paper, we propose and evaluate an active storage system that allows data analysis, mining, and statistical operations to be executed from within a parallel I/O interface. In our proposed scheme, common analysis kernels are embedded in parallel file systems. We expose the semantics of these kernels to parallel file systems through an enhanced runtime interface so that execution of embedded kernels is possible on the server. In order to allow complete server-side operations without file format or layout manipulation, our scheme adjusts the file I/O buffer to the computational unit boundary on the fly. Our scheme also uses server-side collective communication primitives for reduction and aggregation using interserver communication. We have implemented a prototype of our active storage system and demonstrate its benefits using four data analysis benchmarks. Our experimental results show that our proposed system improves the overall performance of all four benchmarks by 50.9% on average and that the compute-intensive portion of the k-means clustering kernel can be improved by 58.4% through GPU offloading when executed with a larger computational load. We also show that our scheme consistently outperforms the traditional storage model with a wide variety of input dataset sizes, number of nodes, and computational loads.
{"title":"Enabling active storage on parallel I/O software stacks","authors":"S. Son, S. Lang, P. Carns, R. Ross, R. Thakur, Berkin Özisikyilmaz, Prabhat Kumar, W. Liao, A. Choudhary","doi":"10.1109/MSST.2010.5496981","DOIUrl":"https://doi.org/10.1109/MSST.2010.5496981","url":null,"abstract":"As data sizes continue to increase, the concept of active storage is well fitted for many data analysis kernels. Nevertheless, while this concept has been investigated and deployed in a number of forms, enabling it from the parallel I/O software stack has been largely unexplored. In this paper, we propose and evaluate an active storage system that allows data analysis, mining, and statistical operations to be executed from within a parallel I/O interface. In our proposed scheme, common analysis kernels are embedded in parallel file systems. We expose the semantics of these kernels to parallel file systems through an enhanced runtime interface so that execution of embedded kernels is possible on the server. In order to allow complete server-side operations without file format or layout manipulation, our scheme adjusts the file I/O buffer to the computational unit boundary on the fly. Our scheme also uses server-side collective communication primitives for reduction and aggregation using interserver communication. We have implemented a prototype of our active storage system and demonstrate its benefits using four data analysis benchmarks. Our experimental results show that our proposed system improves the overall performance of all four benchmarks by 50.9% on average and that the compute-intensive portion of the k-means clustering kernel can be improved by 58.4% through GPU offloading when executed with a larger computational load. We also show that our scheme consistently outperforms the traditional storage model with a wide variety of input dataset sizes, number of nodes, and computational loads.","PeriodicalId":350968,"journal":{"name":"2010 IEEE 26th Symposium on Mass Storage Systems and Technologies (MSST)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125521073","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2010-05-03DOI: 10.1109/MSST.2010.5496973
Richard P. Spillane, S. Dixit, Shrikar Archak, Saumitra Bhanage, E. Zadok
The modern file system is still implemented in the kernel, and is statically linked with other kernel components. This architecture has brought performance and efficient integration with memory management. However kernel development is slow and modern storage systems must support an array of features, including distribution across a network, tagging, searching, deduplication, checksumming, snap-shotting, file pre-allocation, real time I/O guarantees for media, and more. To move complex components into user-level however will require an efficient mechanism for handling page faulting and zero-copy caching, write ordering, synchronous flushes, interaction with the kernel page write-back thread, and secure shared memory. We implement such a system, and experiment with a user-level object store built on top. Our object store is a complete re-design of the traditional storage stack and demonstrates the efficiency of our technique, and the flexibility it grants to user-level storage systems. Our current prototype file system incurs between a 1% and 6% overhead on the default native file system Ext3 for in-cache system workloads. Where the native kernel file system design has traditionally found its primary motivation. For update and insert intensive metadata workloads that are out-of-cache, we perform 39 times better than the native Ext3 file system, while still performing only 2 times worse on out-of-cache random lookups.
{"title":"Exporting kernel page caching for efficient user-level I/O","authors":"Richard P. Spillane, S. Dixit, Shrikar Archak, Saumitra Bhanage, E. Zadok","doi":"10.1109/MSST.2010.5496973","DOIUrl":"https://doi.org/10.1109/MSST.2010.5496973","url":null,"abstract":"The modern file system is still implemented in the kernel, and is statically linked with other kernel components. This architecture has brought performance and efficient integration with memory management. However kernel development is slow and modern storage systems must support an array of features, including distribution across a network, tagging, searching, deduplication, checksumming, snap-shotting, file pre-allocation, real time I/O guarantees for media, and more. To move complex components into user-level however will require an efficient mechanism for handling page faulting and zero-copy caching, write ordering, synchronous flushes, interaction with the kernel page write-back thread, and secure shared memory. We implement such a system, and experiment with a user-level object store built on top. Our object store is a complete re-design of the traditional storage stack and demonstrates the efficiency of our technique, and the flexibility it grants to user-level storage systems. Our current prototype file system incurs between a 1% and 6% overhead on the default native file system Ext3 for in-cache system workloads. Where the native kernel file system design has traditionally found its primary motivation. For update and insert intensive metadata workloads that are out-of-cache, we perform 39 times better than the native Ext3 file system, while still performing only 2 times worse on out-of-cache random lookups.","PeriodicalId":350968,"journal":{"name":"2010 IEEE 26th Symposium on Mass Storage Systems and Technologies (MSST)","volume":"134 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128538091","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2010-05-03DOI: 10.1109/MSST.2010.5496978
Qiang Zoll, Yifeng Zhu, D. Feng
A challenging issue in performance evaluation of parallel storage systems through trace-driven simulation is to accurately characterize and emulate I/O behaviors in real applications. The correlation study of inter-arrival times between I/O requests, with an emphasis on I/O-intensive scientific applications, shows the necessity to further study the self-similarity of parallel I/O arrivals. This paper analyzes several I/O traces collected in large-scale supercomputers and concludes that parallel I/Os exhibit statistically self-similar like behavior. Instead of Markov model, a new stochastic model is proposed and validated in this paper to accurately model parallel I/O burstiness. This model can be used to predicting I/O workloads in real systems and generate reliable synthetic I/O sequences in simulation studies.
{"title":"A study of self-similarity in parallel I/O workloads","authors":"Qiang Zoll, Yifeng Zhu, D. Feng","doi":"10.1109/MSST.2010.5496978","DOIUrl":"https://doi.org/10.1109/MSST.2010.5496978","url":null,"abstract":"A challenging issue in performance evaluation of parallel storage systems through trace-driven simulation is to accurately characterize and emulate I/O behaviors in real applications. The correlation study of inter-arrival times between I/O requests, with an emphasis on I/O-intensive scientific applications, shows the necessity to further study the self-similarity of parallel I/O arrivals. This paper analyzes several I/O traces collected in large-scale supercomputers and concludes that parallel I/Os exhibit statistically self-similar like behavior. Instead of Markov model, a new stochastic model is proposed and validated in this paper to accurately model parallel I/O burstiness. This model can be used to predicting I/O workloads in real systems and generate reliable synthetic I/O sequences in simulation studies.","PeriodicalId":350968,"journal":{"name":"2010 IEEE 26th Symposium on Mass Storage Systems and Technologies (MSST)","volume":"138 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133209721","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2010-05-03DOI: 10.1109/MSST.2010.5496972
K. Shvachko, Hairong Kuang, S. Radia, R. Chansler
The Hadoop Distributed File System (HDFS) is designed to store very large data sets reliably, and to stream those data sets at high bandwidth to user applications. In a large cluster, thousands of servers both host directly attached storage and execute user application tasks. By distributing storage and computation across many servers, the resource can grow with demand while remaining economical at every size. We describe the architecture of HDFS and report on experience using HDFS to manage 25 petabytes of enterprise data at Yahoo!.
{"title":"The Hadoop Distributed File System","authors":"K. Shvachko, Hairong Kuang, S. Radia, R. Chansler","doi":"10.1109/MSST.2010.5496972","DOIUrl":"https://doi.org/10.1109/MSST.2010.5496972","url":null,"abstract":"The Hadoop Distributed File System (HDFS) is designed to store very large data sets reliably, and to stream those data sets at high bandwidth to user applications. In a large cluster, thousands of servers both host directly attached storage and execute user application tasks. By distributing storage and computation across many servers, the resource can grow with demand while remaining economical at every size. We describe the architecture of HDFS and report on experience using HDFS to manage 25 petabytes of enterprise data at Yahoo!.","PeriodicalId":350968,"journal":{"name":"2010 IEEE 26th Symposium on Mass Storage Systems and Technologies (MSST)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124924400","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2010-05-03DOI: 10.1109/MSST.2010.5496995
Hyotaek Shim, Bon-Keun Seo, Jin-Soo Kim, S. Maeng
Recently, NAND flash-based Solid State Drives (SSDs) have been rapidly adopted in laptops, desktops, and server storage systems because their performance is superior to that of traditional magnetic disks. However, NAND flash memory has some limitations such as out-of-place updates, bulk erase operations, and a limited number of write operations. To alleviate these unfavorable characteristics, various techniques for improving internal software and hardware components have been devised. In particular, the internal device cache of SSDs has a significant impact on the performance. The device cache is used for two main purposes: to absorb frequent read/write requests and to store logical-to-physical address mapping information. In the device cache, we observed that the optimal ratio of the data buffering and the address mapping space changes according to workload characteristics. To achieve optimal performance in SSDs, the device cache should be appropriately partitioned between the two main purposes. In this paper, we propose an adaptive partitioning scheme, which is based on a ghost caching mechanism, to adaptively tune the ratio of the buffering and the mapping space in the device cache according to the workload characteristics. The simulation results demonstrate that the performance of the proposed scheme approximates the best performance.
{"title":"An adaptive partitioning scheme for DRAM-based cache in Solid State Drives","authors":"Hyotaek Shim, Bon-Keun Seo, Jin-Soo Kim, S. Maeng","doi":"10.1109/MSST.2010.5496995","DOIUrl":"https://doi.org/10.1109/MSST.2010.5496995","url":null,"abstract":"Recently, NAND flash-based Solid State Drives (SSDs) have been rapidly adopted in laptops, desktops, and server storage systems because their performance is superior to that of traditional magnetic disks. However, NAND flash memory has some limitations such as out-of-place updates, bulk erase operations, and a limited number of write operations. To alleviate these unfavorable characteristics, various techniques for improving internal software and hardware components have been devised. In particular, the internal device cache of SSDs has a significant impact on the performance. The device cache is used for two main purposes: to absorb frequent read/write requests and to store logical-to-physical address mapping information. In the device cache, we observed that the optimal ratio of the data buffering and the address mapping space changes according to workload characteristics. To achieve optimal performance in SSDs, the device cache should be appropriately partitioned between the two main purposes. In this paper, we propose an adaptive partitioning scheme, which is based on a ghost caching mechanism, to adaptively tune the ratio of the buffering and the mapping space in the device cache according to the workload characteristics. The simulation results demonstrate that the performance of the proposed scheme approximates the best performance.","PeriodicalId":350968,"journal":{"name":"2010 IEEE 26th Symposium on Mass Storage Systems and Technologies (MSST)","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131042506","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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